input: Write a python function to create and fit a linear regression model using the given input data and make a prediction for a new data point.
  assert round(predict([[1, 1], [2, 2], [3, 3], [4, 4]], [5, 5], [5, 10, 15, 20]), 2) == 25.0
  assert round(predict([[1, 2], [2, 3], [3, 4], [4, 5]], [5, 6], [3, 7, 11, 15]), 2) == 19.0
output: def predict(X_train, X_test, y_train):
      from sklearn.linear_model import LinearRegression
      
      # Create the model
      model = LinearRegression()
      
      # Fit the model
      model.fit(X_train, y_train)
      
      # Make predictions
      y_pred = model.predict([X_test])
      
      return y_pred[0]