Final answer:
The validation set is utilized to fine-tune a model's performance during cross-validation, following training, and before the final evaluation on the test set.
Step-by-step explanation:
During cross-validation, the validation set is used to tune the performance of a model. After training a model on a training set, the validation set is used to evaluate the model and fine-tune its hyperparameters, without leaking the information from the test set, which is kept aside to assess the final performance of the model as it would perform on unseen data. This process helps in avoiding overfitting and ensures that the model generalizes well to new data.