precision_recall_curve can raise `ValueError: unknown format is not supported` when nullable types are used

The following block of code will work for `pos_label_idx` equal to 1 but raise `ValueError: unknown format is not supported` when `pos_label_idx` is 0:

```python
import woodwork as ww
from evalml.model_understanding.metrics import precision_recall_curve

y_true = pd.Series(np.array([0, 0, 1, 1]))
y_true = ww.init_series(y_true, logical_type="IntegerNullable")
y_predict_proba = pd.DataFrame(
np.array([[0.9, 0.1], [0.6, 0.4], [0.65, 0.35], [0.2, 0.8]]),
)
# Works
precision_recall_curve_data = precision_recall_curve(
y_true,
y_predict_proba,
pos_label_idx=1,
)

# Broken
precision_recall_curve_data = precision_recall_curve(
y_true,
y_predict_proba,
pos_label_idx=0,
)
```

We should look into why this is happening for `pos_label_idx=0` but not `pos_label_idx=1` and add support for nullable types. We should consider using `_convert_ww_series_to_np_array` as we do in `confusion_matrix` to support the nullable type conversion to numpy.

Note - this seems to be related to #3910 , as both have to do with a checking of the type of the target via sklearn's `type_of_target` util returning `unknown` for data that uses nullable pandas dtypes.