Underfitting

Underfitting happens when your model is too simple to capture the underlying patterns in your training data. It's like a chef who only knows how to boil water; they can't even cook basic meals well. This results in poor performance not just on new data, but often on the training data itself, indicating the model hasn't learned enough.