BUG Wrong error raised for OneVsRestClassifier with a sub-estimator that doesn't allow partial_fit

### Describe the bug

When using the `OneVsRestClassifier` with a sub-estimator, that doesn't have `partial_fit` implemented, a misleading error message is shown: `AttributeError: This 'OneVsRestClassifier' has no attribute 'partial_fit'`.

Though, `OneVsRestClassifier` does implement `partial_fit`, but the underlying estimator doesn't.

There is an appropriate error raising already implemented in
https://github.com/scikit-learn/scikit-learn/blob/f1e89363f6777155a25b3574db9f0fc5c21a8c51/sklearn/multiclass.py#L437

```python
            if not hasattr(self.estimator, "partial_fit"):
                raise ValueError(
                    ("Base estimator {0}, doesn't have partial_fit method").format(
                        self.estimator
                    )
                )
```
But it's not run, because the AttributeError from the `@available_if` decorator/descriptor thing pops up earlier.

I'd like to learn about that, repair that and add a test to make sure this doesn't happen again by accident.
I will also check if other methods from the multiclass classifiers are also affected.

Is it alright if I go ahead with this?

### Steps/Code to Reproduce

```python
from sklearn.datasets import load_iris
from sklearn.multiclass import OneVsRestClassifier
from sklearn.linear_model import LogisticRegression
import numpy as np

iris = load_iris()
sample_weight = np.ones_like(iris.target, dtype=np.float64)
clf = OneVsRestClassifier(
estimator=LogisticRegression(random_state=42)
)
clf.partial_fit(iris.data, iris.target)
```

### Expected Results

`ValueError:  LogisticRegression doesn't have partial_fit method`

### Actual Results

`AttributeError: This 'OneVsRestClassifier' has no attribute 'partial_fit'`.

### Versions

```shell
System:
    python: 3.10.6 (main, Oct 10 2022, 12:43:33) [GCC 9.4.0]
executable: /home/stefanie/.pyenv/versions/3.10.6/envs/scikit-learn_dev/bin/python
   machine: Linux-5.15.0-91-generic-x86_64-with-glibc2.31

Python dependencies:
      sklearn: 1.5.dev0
          pip: 23.3.2
   setuptools: 63.2.0
        numpy: 1.26.0
        scipy: 1.11.3
       Cython: 0.29.34
       pandas: 2.1.4
   matplotlib: 3.8.0
       joblib: 1.3.2
threadpoolctl: 3.1.0

Built with OpenMP: True

threadpoolctl info:
       user_api: blas
   internal_api: openblas
         prefix: libopenblas
       filepath: /home/stefanie/.pyenv/versions/3.10.6/envs/scikit-learn_dev/lib/python3.10/site-packages/numpy.libs/libopenblas64_p-r0-0cf96a72.3.23.dev.so
        version: 0.3.23.dev
threading_layer: pthreads
   architecture: SkylakeX
    num_threads: 8

       user_api: blas
   internal_api: openblas
         prefix: libopenblas
       filepath: /home/stefanie/.pyenv/versions/3.10.6/envs/scikit-learn_dev/lib/python3.10/site-packages/scipy.libs/libopenblasp-r0-23e5df77.3.21.dev.so
        version: 0.3.21.dev
threading_layer: pthreads
   architecture: SkylakeX
    num_threads: 8

       user_api: openmp
   internal_api: openmp
         prefix: libgomp
       filepath: /usr/lib/x86_64-linux-gnu/libgomp.so.1.0.0
        version: None
    num_threads: 8
```

COMMENT:
@thomasjpfan Nice, I like it a lot!

Do I understand correctly that working on this PR still makes sense? For now, there is no inner error raised for the five estimators we talk about here and there should be, right?

Labels: Bug