"Nested CV to testing data" is similar to "CV to validation data".
Validation data is used to tune hyperparameters and prevent overfitting.
CV lets us get multiple copies of validation data (ideally different). So we our parameter selection process can be more robust.
Testing data is to used evaluate the performance of the selected model (refit using whole training data with optimal parameters selected by CV).
Outer loop of Nested CV lets us get multiple copies of testing data. Our final model evaluation (such as MSE, AUC) can be more robust.
With above statements, the purpose of Nested CV is to evaluate model performance better, NOT to tune parameters better.
Is anything wrong about my understanding? Thanks!