_get_tags() missing 1 required positional argument: 'self'

### Describe the bug

I made an error when I used RFECV.fit,


### Steps/Code to Reproduce

```python
import pandas as pd
from sklearn.model_selection import StratifiedKFold
import matplotlib.pyplot as plt
from sklearn.feature_selection import RFECV
from sklearn.ensemble import RandomForestClassifier

Y1 = [90.2,90.2,90.2,90.2,90.2,90.2,90.2,20.28,85.03,90.2,85.03,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,20.28,85.03,90.2,90.2,90.2,90.2,90.2,90.2,90.2,85.03,20.28,20.28,85.03,20.28,85.03,85.03,85.03,90.2,90.2,90.2,85.03,90.2,90.2,90.2,90.2,77.36,90.2,90.2,90.2,90.2,90.2,90.2,85.03,90.2,90.2,90.2,90.2,90.2,90.2,90.2,20.28,20.28,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,77.36,90.2,90.2,90.2,90.2,90.2,90.2,85.03,90.2,90.2,90.2,90.2,90.2,20.28,20.28,90.2,90.2,90.2,90.2,90.2,90.2,20.28,85.03,90.2,90.2,90.2,90.2,90.2,90.2,90.2,20.28,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,20.28,20.28,20.28,90.2,20.28,90.2,90.2,20.28,90.2,90.2,20.28,85.03,90.2,20.28,90.2,90.2,90.2,90.2,20.28,90.2,90.2,20.28,20.28,90.2,90.2,20.28,20.28,20.28,20.28,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,20.28,20.28,90.2,90.2,90.2,90.2,90.2,90.2,20.28,90.2,90.2,20.28,20.28,85.03,85.03,85.03,85.03,85.03,20.28,90.2,20.28,85.03,85.03,20.28,85.03,90.2,90.2,20.28,90.2,85.03,20.28,90.2,85.03,90.2,90.2,90.2,20.28,90.2,90.2,20.28,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,85.03,20.28,90.2,85.03,90.2,20.28,85.03,90.2,20.28,90.2,90.2,85.03,90.2,90.2,20.28,90.2,90.2,90.2,90.2,90.2,90.2,20.28,90.2,85.03,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,20.28,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,20.28,20.28,90.2,20.28,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,20.28,90.2,20.28,20.28,85.03,85.03,90.2,90.2,90.2,90.2,20.28,90.2,20.28,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,90.2,85.03,20.28,90.2,85.03,85.03,90.2,90.2,90.2,20.28,90.2,90.2,85.03,85.03,85.03,20.28,85.03,20.28,20.28,20.28,90.2,85.03,85.03,90.2,90.2,85.03,20.28,90.2,85.03,85.03,90.2,90.2,90.2,90.2,85.03,20.28,85.03]
Y2 = [2231.55,1994.64,2187.0620000000004,1533.3,1603.7333333333333,2489.8,2783.3,1620.12,1507.5575,1413.55,1636.3075,2672.8,2153.4,2184.3,2104.0666666666666,1661.05,1413.55,2388.4,2153.4,2153.4,2047.05,1692.3999999999999,2085.05,1620.12,1507.5575,1390.3274999999999,2089.3,2012.0666666666666,2153.4,1661.05,2360.733333333333,1725.7333333333333,1334.0575,893.3116666666666,1326.9316666666666,1867.4460000000004,1261.3179999999998,1270.2459999999999,1654.7050000000002,1533.0575,1725.7333333333333,1669.3333333333333,2131.05,1636.3075,2104.0666666666666,2311.0666666666666,2085.05,2293.55,1091.1866666666667,2472.05,2626.0666666666666,1739.3999999999999,2252.8,1739.3999999999999,2042.3999999999999,1533.0575,2042.3999999999999,1750.3999999999999,2042.3999999999999,2231.55,2042.3999999999999,2042.3999999999999,1744.2620000000002,894.574,894.574,1697.8,2089.3,1521.0,1651.0666666666666,1677.7333333333333,1504.3,2268.4,1374.3,2386.8,1452.8,2252.8,1617.0666666666666,1617.0666666666666,1528.05,1788.7333333333333,1520.32,1497.8,1603.7333333333333,1603.7333333333333,1476.6619999999998,1788.7333333333333,1900.8,1788.7333333333333,1346.05,1612.12,1682.3,1383.05,1847.05,2290.4,2074.05,1491.8,1603.7333333333333,1865.3,1900.8,1651.0666666666666,1990.3,1677.7333333333333,1458.7333333333333,1677.7333333333333,1568.462,1603.7333333333333,2668.3,1677.7333333333333,1352.05,1865.3,1076.3899999999999,2396.3,1949.8,1734.3,1541.0,1744.7333333333333,1655.75,1497.5575,1655.75,2107.05,2360.8,2089.3,1661.05,1620.12,1436.8266666666666,2633.0666666666666,1753.3,2074.3,1968.3999999999999,1968.3999999999999,1624.55,1536.87,1553.0575,1594.8,1473.0774999999999,2660.3,1981.7333333333333,2104.0666666666666,2153.4,2360.8,1366.62,2392.3,1968.3999999999999,2171.8,1650.05,1624.55,1890.05,2018.8,1904.05,1473.0774999999999,2517.3,1981.7333333333333,2246.05,1716.3,1753.3,2015.7333333333333,2263.8,2047.05,1971.05,2215.05,1945.55,1546.0774999999999,1418.37,1481.37,1481.37,1998.3,1366.62,2153.4,2016.05,1516.87,2016.05,2232.8,1491.37,1599.3075,2107.05,1516.87,2193.05,1847.05,1637.8274999999999,2153.4,1620.12,2089.3,1712.3,1436.8266666666666,1516.87,1968.3999999999999,2396.3,1436.8266666666666,1366.62,1335.62,1481.37,1968.3999999999999,2246.05,1753.3,2396.3,2105.55,1499.8,2015.7333333333333,1799.8,1836.8,2388.55,1674.8274999999999,2313.05,1614.3999999999999,1624.55,2517.3,1847.05,1744.7333333333333,1753.3,1261.3179999999998,1418.37,1712.3,2010.8,1744.7333333333333,1255.822,1655.75,2018.8,1366.62,1541.0,1826.44,1066.368,1021.128,1654.646,1629.846,1867.4460000000004,1867.4460000000004,1640.0459999999998,1549.696,1241.6219999999998,837.645,1192.0459999999998,2282.0383333333334,1067.9019999999998,1629.846,1790.0333333333335,1570.7,988.168,2109.2400000000002,1857.4460000000004,1435.9679999999998,1509.5333333333335,1507.5575,2209.8,2252.8,2360.733333333333,1317.87,1981.7333333333333,1968.3999999999999,1366.62,1968.3999999999999,2360.733333333333,1569.3,1765.3,1674.8274999999999,1698.05,1744.3,1734.3,1533.0575,1366.62,1744.3,1497.5575,1873.05,1335.62,1153.585,1614.3999999999999,1335.62,2252.8,1546.0775,1533.0575,1624.55,1712.3,1536.87,1671.3,2028.55,2028.55,2015.7333333333333,1744.7333333333333,2104.0666666666666,1144.87,1352.05,880.085,2418.8,1491.8,1195.3,1923.8,1352.05,1349.8,2107.05,1412.0666666666666,1504.3,2311.3,1718.3,1580.6,1553.05,1651.0666666666666,1739.3999999999999,1267.5,2489.8,2386.8,1450.7333333333333,2430.8,1599.55,1788.7333333333333,1533.3,1990.3,1685.3999999999999,2060.3,1409.3999999999999,1642.05,1217.87,1450.7333333333333,1739.3999999999999,1226.3,2107.05,1520.32,1677.7333333333333,1346.05,1617.0666666666666,2431.6620000000003,2268.4,1587.04,1739.3999999999999,1462.8,1507.8,1677.7333333333333,1677.7333333333333,1619.8,1409.3999999999999,1900.8,1636.55,1522.05,1822.05,1739.3999999999999,1716.55,1800.8,2360.733333333333,1473.0774999999999,1712.3,1795.55,2104.0666666666666,1777.8,1765.3,1716.55,1800.8,1712.3,2360.733333333333,1335.62,1516.87,1744.7333333333333,1335.62,1981.7333333333333,2089.3,2633.0666666666666,1981.7333333333333,1968.3999999999999,1851.05,1716.55,2042.3999999999999,2028.55,2016.05,1499.8,2153.4,1516.87,2215.05,1335.62,1491.37,1599.3075,1507.5575,1725.7333333333333,1769.8,1744.3,1749.3999999999999,1516.87,2360.8,1096.96,1712.3,1653.55,1750.3999999999999,2012.0666666666666,1421.3274999999999,1752.05,2171.8,1747.8,2105.55,1744.7333333333333,1960.8,1153.6499999999999,1495.24,1677.7333333333333,1553.55,1779.3075,1979.87,2042.3999999999999,1434.5575,1497.5575,1968.3999999999999,1510.0,1815.3999999999999,1481.37,1255.822,2153.6400000000003,1671.7050000000002,1612.2459999999999,1549.446,1800.8960000000002,1629.846,1563.896,1549.696,1841.58,1762.8400000000001,1632.046,1540.246,1388.6399999999999,1392.04,1612.2459999999999,1536.4959999999999,1790.0333333333335,1615.646,1612.2459999999999,1595.3666666666668,1329.262,1737.5333333333335,1774.551666666667,1712.0328571428574,1701.6557142857146,1638.4614285714288]
Y3 = [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]

data = pd.DataFrame([Y1, Y2, Y3]).T

data.columns = ['min', 'max', 'quality']

X = data.loc[:,data.columns != 'quality']
y = data.loc[:,data.columns == 'quality']

min_features_to_select = 1  # Minimum number of features to consider

rfecv = RFECV(
    estimator=RandomForestClassifier,
    step=1,
    cv=StratifiedKFold(2),
    scoring="accuracy",
    min_features_to_select=min_features_to_select, 
)
rfecv.fit(X.values, y.values)

print("Optimal number of features : %d" % rfecv.n_features_)

# Plot number of features VS. cross-validation scores
plt.figure()
plt.xlabel("Number of features selected")
plt.ylabel("Cross validation score (accuracy)")
plt.plot(
    range(min_features_to_select, len(rfecv.grid_scores_) + min_features_to_select),
    rfecv.grid_scores_,
)
plt.show()
```

### Expected Results

No error is thrown.

### Actual Results

TypeError                                 Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_69848/1460406303.py in <module>
      8     min_features_to_select=min_features_to_select,
      9 )
---> 10 rfecv.fit(X.values, y.values)
     11 
     12 print("Optimal number of features : %d" % rfecv.n_features_)

D:\anaconda3\lib\site-packages\sklearn\feature_selection\_rfe.py in fit(self, X, y, groups)
    671             Fitted estimator.
    672         """
--> 673         tags = self._get_tags()
    674         X, y = self._validate_data(
    675             X,

D:\anaconda3\lib\site-packages\sklearn\base.py in _get_tags(self)
    353                 # but might do redundant work in estimators
    354                 # (i.e. calling more tags on BaseEstimator multiple times)
--> 355                 more_tags = base_class._more_tags(self)
    356                 collected_tags.update(more_tags)
    357         return collected_tags

D:\anaconda3\lib\site-packages\sklearn\feature_selection\_rfe.py in _more_tags(self)
    443         return {
    444             "poor_score": True,
--> 445             "allow_nan": _safe_tags(self.estimator, key="allow_nan"),
    446             "requires_y": True,
    447         }

D:\anaconda3\lib\site-packages\sklearn\utils\_tags.py in _safe_tags(estimator, key)
     50     if hasattr(estimator, "_get_tags"):
     51         tags_provider = "_get_tags()"
---> 52         tags = estimator._get_tags()
     53     elif hasattr(estimator, "_more_tags"):
     54         tags_provider = "_more_tags()"

TypeError: _get_tags() missing 1 required positional argument: 'self'

### Versions

```shell
System:
    python: 3.9.7 (default, Sep 16 2021, 16:59:28) [MSC v.1916 64 bit (AMD64)]
executable: D:\anaconda3\python.exe
   machine: Windows-10-10.0.22000-SP0

Python dependencies:
      sklearn: 1.1.1
          pip: 21.2.4
   setuptools: 58.0.4
        numpy: 1.22.4
        scipy: 1.7.1
       Cython: 0.29.24
       pandas: 1.4.2
   matplotlib: 3.4.3
       joblib: 1.1.0
threadpoolctl: 2.2.0

Built with OpenMP: True
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_10704/1160322016.py in <module>
----> 1 sklearn.show_versions()

D:\anaconda3\lib\site-packages\sklearn\utils\_show_versions.py in show_versions()
    118 
    119     # show threadpoolctl results
--> 120     threadpool_results = threadpool_info()
    121     if threadpool_results:
    122         print()

D:\anaconda3\lib\site-packages\sklearn\utils\fixes.py in threadpool_info()
    160         return controller.info()
    161     else:
--> 162         return threadpoolctl.threadpool_info()
    163 
    164 

D:\anaconda3\lib\site-packages\threadpoolctl.py in threadpool_info()
    122     In addition, each module may contain internal_api specific entries.
    123     """
--> 124     return _ThreadpoolInfo(user_api=_ALL_USER_APIS).todicts()
    125 
    126 

D:\anaconda3\lib\site-packages\threadpoolctl.py in __init__(self, user_api, prefixes, modules)
    338 
    339             self.modules = []
--> 340             self._load_modules()
    341             self._warn_if_incompatible_openmp()
    342         else:

D:\anaconda3\lib\site-packages\threadpoolctl.py in _load_modules(self)
    371             self._find_modules_with_dyld()
    372         elif sys.platform == "win32":
--> 373             self._find_modules_with_enum_process_module_ex()
    374         else:
    375             self._find_modules_with_dl_iterate_phdr()

D:\anaconda3\lib\site-packages\threadpoolctl.py in _find_modules_with_enum_process_module_ex(self)
    483 
    484                 # Store the module if it is supported and selected
--> 485                 self._make_module_from_path(filepath)
    486         finally:
    487             kernel_32.CloseHandle(h_process)

D:\anaconda3\lib\site-packages\threadpoolctl.py in _make_module_from_path(self, filepath)
    513             if prefix in self.prefixes or user_api in self.user_api:
    514                 module_class = globals()[module_class]
--> 515                 module = module_class(filepath, prefix, user_api, internal_api)
    516                 self.modules.append(module)
    517 

D:\anaconda3\lib\site-packages\threadpoolctl.py in __init__(self, filepath, prefix, user_api, internal_api)
    604         self.internal_api = internal_api
    605         self._dynlib = ctypes.CDLL(filepath, mode=_RTLD_NOLOAD)
--> 606         self.version = self.get_version()
    607         self.num_threads = self.get_num_threads()
    608         self._get_extra_info()

D:\anaconda3\lib\site-packages\threadpoolctl.py in get_version(self)
    644                              lambda: None)
    645         get_config.restype = ctypes.c_char_p
--> 646         config = get_config().split()
    647         if config[0] == b"OpenBLAS":
    648             return config[1].decode("utf-8")

AttributeError: 'NoneType' object has no attribute 'split'
```

COMMENT:
`RFECV` requires an instantiated estimator: 

```python
rfecv = RFECV(
    estimator=RandomForestClassifier(),
    ...
)
```

This allows one to also configure the `estimator`:

```python
rfecv = RFECV(
    estimator=RandomForestClassifier(max_depth=3),
    ...
)
```

Labels: Bug, Needs Triage