input: def naive_bayes_classifier_for_emails() -> GaussianNB:
      """Construct a naive Bayes classifier using Python's sklearn library to classify emails as spam or not spam.
      The function instantiates a GaussianNB classifier, fits it to the training data, and predicts the outcomes on the test data.
      
      Example:
      >>> X_train = [[0, 0], [1, 1], [2, 2]]
      >>> y_train = [0, 1, 1]
      >>> X_test = [[3, 3]]
      >>> model = naive_bayes_classifier_for_emails()
      >>> model.predict(X_test)
      [1]
      """
output:     from sklearn.naive_bayes import GaussianNB
  
      model = GaussianNB()
      return model