A validation dataset is a subset of data used to evaluate the performance of a machine learning model during training. It helps to fine-tune the model by providing feedback on how well it generalizes to unseen data. This dataset is separate from the training dataset, which is used to teach the model. By using a validation dataset, developers can adjust model parameters and avoid overfitting, where the model performs well on training data but poorly on new data. This process is crucial for ensuring that the model, such as those used in artificial intelligence applications, is reliable and effective in real-world scenarios.