Learning curves can help identify overfitting and underfitting in machine learning models. Overfitting occurs when a model performs well on the training data but poorly on unseen data, while underfitting is when a model performs poorly on both training and unseen data. By analyzing the learning curves, developers can detect these issues and adjust the model's complexity or the amount of training data to improve its performance.