Imbalanced datasets can cause machine learning models to be biased towards the majority class. This can lead to poorer performance on the minority class, and ultimately to poorer overall performance on the dataset as a whole. To avoid this, it is important to either balance the dataset before training the model, or to use a model that is designed to handle imbalanced datasets.
