input: from typing import List
  
  def binary_classification_model(X: List[List[float]], y: List[int]) -> None:
      """
      Implement a basic machine learning model that performs binary classification on the given data.
      The model should use Logistic Regression from scikit-learn and print the accuracy of the model on the training data.
      Example:
      >>> X = [[0.3, 0.2, 0.6], [0.3, 0.1, 0.4], [0.2, 0.3, 0.4], [0.7, 0.4, 0.2], [0.5, 0.2, 0.1]]
      >>> y = [1, 0, 0, 1, 0]
      >>> binary_classification_model(X, y)
      Model accuracy: 1.0
      """
      pass
output:     from sklearn.linear_model import LogisticRegression
      from sklearn.metrics import accuracy_score
  
      model = LogisticRegression()
      model.fit(X, y)
      y_pred = model.predict(X)
      accuracy = accuracy_score(y, y_pred)
      print(f"Model accuracy: {accuracy}")