input: Write a python function to train a Support Vector Classifier (SVC) using given training data and evaluate its accuracy using given test data.
  assert train_and_evaluate_svc(X_train, y_train, X_test, y_test) == accuracy
  assert train_and_evaluate_svc(X_train_sample, y_train_sample, X_test_sample, y_test_sample) == sample_accuracy
output: def train_and_evaluate_svc(X_train, y_train, X_test, y_test):
      from sklearn.svm import SVC
      from sklearn.metrics import accuracy_score
  
      # Create and train the Support Vector Classifier
      svc = SVC()
      svc.fit(X_train, y_train)
  
      # Predict on the test data
      y_pred = svc.predict(X_test)
  
      # Calculate and return the accuracy
      accuracy = accuracy_score(y_test, y_pred)
      return accuracy