input: Write a python function to perform 5-fold cross-validation using KNeighborsClassifier on a given dataset.
  ```python
  assert len(kfold_cross_validation(X, y)) == 5
  assert all(isinstance(score, float) for score in kfold_cross_validation(X, y))
  assert all(0 <= score <= 1 for score in kfold_cross_validation(X, y))
output: from sklearn.model_selection import KFold
  from sklearn.neighbors import KNeighborsClassifier
  from sklearn.metrics import accuracy_score
  
  def kfold_cross_validation(X, y):
      kf = KFold(n_splits=5)
      scores = []
      
      for train_index, test_index in kf.split(X):
          X_train, X_test = X[train_index], X[test_index]
          y_train, y_test = y[train_index], y[test_index]
          
          model = KNeighborsClassifier()
          model.fit(X_train, y_train)
          y_pred = model.predict(X_test)
          
          scores.append(accuracy_score(y_test, y_pred))
      
      return scores