Verbosity option is not working in GridSearchCV (Jupyter notebook)

### Describe the bug

So this issue has been addressed before [here ](https://github.com/scikit-learn/scikit-learn/issues/22291) by [darrencl](https://github.com/darrencl), but the user didn't follow up with [lesteve](https://github.com/lesteve) response.

The problem is that GridSearchCV doesn't show the elapsed time periodically, or any log, I am set`n_jobs = -1`, and `verbose = 1`. I tried setting `n_jobs` to other values, the same with `verbose`, but nothing happened.
Note that this didn't happen until I updated scikit-learn from version 0.22.1 to 1.0.2.

[lesteve](https://github.com/lesteve) in his response assumed that this problem is due to `ipykernel <6`, which is not the case with me.

### Steps/Code to Reproduce

```
from sklearn.model_selection import GridSearchCV
from sklearn.ensemble import RandomForestClassifier
from sklearn import datasets

iris = datasets.load_iris()
params = {'n_estimators':[10,20,30,40,50,60],
          'max_depth':[20,50,60,70,80]}
grid_obj = GridSearchCV(estimator=RandomForestClassifier(), param_grid=params, n_jobs=-1, verbose=1, cv=5)
grid_obj.fit(iris.data, iris.target)
```

### Expected Results

This is the output when using version 0.22.1
![image](https://user-images.githubusercontent.com/17684093/158401635-31755363-2108-41e7-8f7f-08985abd03b8.png)


### Actual Results

```Fitting 5 folds for each of 30 candidates, totalling 150 fits```

### Versions

```shell
System:
    python: 3.8.5 (default, Sep  3 2020, 21:29:08) [MSC v.1916 64 bit (AMD64)]
executable: D:\Programs\ApplicationsSetup\anaconda3\python.exe
   machine: Windows-10-10.0.19041-SP0

Python dependencies:
          pip: 21.2.2
   setuptools: 58.0.4
      sklearn: 1.0.2
        numpy: 1.19.2
        scipy: 1.6.2
       Cython: 0.29.25
       pandas: 1.4.1
   matplotlib: 3.5.1
       joblib: 1.1.0
threadpoolctl: 2.2.0


!jupyter --version
Selected Jupyter core packages...
IPython          : 7.31.1
ipykernel        : 6.4.1
ipywidgets       : 7.6.5
jupyter_client   : 6.1.12
jupyter_core     : 4.9.1
jupyter_server   : 1.13.5
jupyterlab       : 3.2.9
nbclient         : 0.5.11
nbconvert        : 6.1.0
nbformat         : 5.1.3
notebook         : 6.4.9
qtconsole        : 5.2.2
traitlets        : 5.1.1
```

COMMENT:
I also been stuck with a similar issue for a good while - I was trying to make the progress in my GridSearchCV to be displayed at least at *some* realtime manner inside my notebook. Finally, I was able to reach the goal - by combining the `%env PYTHONUNBUFFERED=1` with a multiprocessing approach above.

This method allows you to encapsulate the unbuffered output only for a desired cell, instead of forcing it instance-wide (e.g. `PYTHONUNBUFFERED=1`). Hope it helps someone.

Example of code:

```
%env PYTHONUNBUFFERED=1
from joblib import parallel_backend
from sklearn.model_selection import GridSearchCV
grid = GridSearchCV(pipeline, param_grid=param_grid, scoring='accuracy', cv=3, n_jobs=-1, verbose=2)
with parallel_backend('multiprocessing'):
  grid.fit(x_train, y_train)
```

Example of a result:

<img width="1057" alt="Image" src="https://github.com/user-attachments/assets/a1c5043d-d2bb-45c8-b152-9c9bdabeb7df" />

Labels: Bug, module:model_selection, Needs Investigation