What is underfitting in machine learning?

A When a model's predictions are consistently biased in one direction due to poor data collection B When a model is too simple to capture the underlying patterns in the data, resulting in poor performance on both training and test sets C When a model memorizes training data and fails on new examples D When a model is trained on too many features and loses predictive power