Unknown label type: 'continuous' error when training kNN

I'm teaching the nearest neighbor method.
On a regular DataFrame of attributes, everything works well. But, when I scale the signs, an error occurs.

Here is the code:

y = data['Sort'].astype(float)
X = data.drop('Sort', axis=1)
X = data.astype(float)
X_scale = sk.preprocessing.scale(X)
y_scale = sk.preprocessing.scale(y)

I output the optimal number of neighbors and the evaluation of the algorithm:

kMeans_scale = []
for k in range(1,51):
    kn = KNeighborsClassifier(n_neighbors=k)
    kn.fit(X_scale, y_scale)
    array = cross_val_score(estimator = kn, X=X_scale, y=y_scale, cv=kf, scoring = 'accuracy')
    kMeans_scale.append(m)
m = max(kMeans_scale)
print(np.round(m,decimals = 2))
s = kMeans_scale.index(m)
print(s+1)

Mistake:

ValueError                                Traceback (most recent call last)
<ipython-input-134-af5b3598c259> in <module>
      2 for k in range(1,51):
      3     kn = KNeighborsClassifier(n_neighbors=k)
----> 4     kn.fit(X_scale, y_scale)
      5     array = cross_val_score(estimator = kn, X=X_scale, y=y_scale, cv=kf, scoring = 'accuracy')
      6     kMeans_scale.append(m)

~\Anaconda3\lib\site-packages\sklearn\neighbors\base.py in fit(self, X, y)
    903             self.outputs_2d_ = True
    904 
--> 905         check_classification_targets(y)
    906         self.classes_ = []
    907         self._y = np.empty(y.shape, dtype=np.int)

~\Anaconda3\lib\site-packages\sklearn\utils\multiclass.py in check_classification_targets(y)
    169     if y_type not in ['binary', 'multiclass', 'multiclass-multioutput',
    170                       'multilabel-indicator', 'multilabel-sequences']:
--> 171         raise ValueError("Unknown label type: %r" % y_type)
    172 
    173 

What can this be related to?

ValueError: Unknown label type: 'continuous'