Attribute error from `sklearn.base.is_regressor` due to missing `__sklearn_tags__` on nightly builds

### Describe the bug

Running the following script works without a warning in sklearn 1.7, but fails on the latest nightly release. It appears to be related to https://github.com/scikit-learn/scikit-learn/pull/31134, but I'm unsure why the issue only became apparent now.

### Steps/Code to Reproduce

```python
from sklearn.base import is_regressor

class MyEstimator:
    def __init__(self):
        ...

    def fit(self, X, y=None):
        self.is_fitted_ = True
        return self

    def predict(self, X):
        ...


est = MyEstimator()
is_regressor(est)
```

### Expected Results

I would expect the code to continue to run, possibly with a `DeprecationWarning`.

### Actual Results

```
Traceback (most recent call last):
  File "/Users/christian.bourjau/repos/scikit-learn-debug/.pixi/envs/nightlies/lib/python3.12/site-packages/sklearn/utils/_tags.py", line 275, in get_tags
    tags = estimator.__sklearn_tags__()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
AttributeError: 'MyEstimator' object has no attribute '__sklearn_tags__'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/Users/christian.bourjau/repos/scikit-learn-debug/t.py", line 17, in <module>
    is_regressor(est)
  File "/Users/christian.bourjau/repos/scikit-learn-debug/.pixi/envs/nightlies/lib/python3.12/site-packages/sklearn/base.py", line 1238, in is_regressor
    return get_tags(estimator).estimator_type == "regressor"
           ^^^^^^^^^^^^^^^^^^^
  File "/Users/christian.bourjau/repos/scikit-learn-debug/.pixi/envs/nightlies/lib/python3.12/site-packages/sklearn/utils/_tags.py", line 283, in get_tags
    raise AttributeError(
AttributeError: The following error was raised: 'MyEstimator' object has no attribute '__sklearn_tags__'. It seems that there are no classes that implement `__sklearn_tags__` in the MRO and/or all classes in the MRO call `super().__sklearn_tags__()`. Make sure to inherit from `BaseEstimator` which implements `__sklearn_tags__` (or alternatively define `__sklearn_tags__` but we don't recommend this approach). Note that `BaseEstimator` needs to be on the right side of other Mixins in the inheritance order.
```

### Versions

```shell
System:
    python: 3.12.11 | packaged by conda-forge | (main, Jun  4 2025, 14:38:53) [Clang 18.1.8 ]
executable: /Users/christian.bourjau/repos/scikit-learn-debug/.pixi/envs/nightlies/bin/python
   machine: macOS-15.6.1-arm64-arm-64bit

Python dependencies:
      sklearn: 1.8.dev0
          pip: 25.2
   setuptools: 80.9.0
        numpy: 2.2.6
        scipy: 1.16.0
       Cython: 3.1.2
       pandas: 3.0.0.dev0+2502.g8476e0f756
   matplotlib: None
       joblib: 1.5.1
threadpoolctl: 3.6.0

Built with OpenMP: True

threadpoolctl info:
       user_api: blas
   internal_api: openblas
    num_threads: 16
         prefix: libopenblas
       filepath: /Users/christian.bourjau/repos/scikit-learn-debug/.pixi/envs/nightlies/lib/libopenblas.0.dylib
        version: 0.3.30
threading_layer: openmp
   architecture: VORTEX

       user_api: openmp
   internal_api: openmp
    num_threads: 16
         prefix: libomp
       filepath: /Users/christian.bourjau/repos/scikit-learn-debug/.pixi/envs/nightlies/lib/libomp.dylib
        version: None

       user_api: openmp
   internal_api: openmp
    num_threads: 16
         prefix: libomp
       filepath: /Users/christian.bourjau/repos/scikit-learn-debug/.pixi/envs/nightlies/lib/python3.12/site-packages/sklearn/.dylibs/libomp.dylib
        version: None
```

COMMENT:
First thanks a lot for testing the scikit-learn development version 🙏! This is super useful to have this kind of feed-back early so we can adjust before the 1.8 release.

cc @jeremiedbb @adrinjalali and @glemaitre who worked on https://github.com/scikit-learn/scikit-learn/pull/31134. Skimming through it very quickly it seems like the intention was a `DeprecationWarning` in 1.8 but maybe I am missing something.

One possible work-around, if you are OK with having a dependency on scikit-learn, is to derive from `BaseEstimator` (and `RegressorMixin` if you want your estimator to be a regressor).

```py
from sklearn.base import is_regressor
from sklearn.base import BaseEstimator

class MyEstimator(BaseEstimator):
    def __init__(self):
        ...

    def fit(self, X, y=None):
        self.is_fitted_ = True
        return self

    def predict(self, X):
        ...


est = MyEstimator()
is_regressor(est)
```

Labels: Bug