Based on our algorithm, there could be different outputs of the training phase. Let's assume that the learned target function is as shown in the following diagram:

This lazy function always predicts a constant output value. Since the target function is not able to learn the underlying structure of the data, it results in what is termed as underfitting. An underfit model has a poor predictive performance.