👉 Underfitting in machine learning refers to a situation where a model's performance is not as good as it could be. It occurs when the model cannot capture the underlying patterns or relationships within the data, leading to poor predictions and less accurate classification results. When an algorithm fails to fit the training data perfectly, it might produce incorrect predictions or even misclassify observations if there are outliers or missing values in the dataset. This can lead to a situation where the model does not perform as well as expected on
