Final answer:
Supervised data mining requires having labeled data for training a model to make predictions or classifications.
Step-by-step explanation:
Supervised data mining refers to the use of labeled data to train a model to make predictions or classifications. The condition that must be met for supervised data mining is that the dataset used for training the model must have pre-determined labels or target values assigned to each data instance.
These labels serve as the ground truth for the model to learn from and make accurate predictions on new, unseen data.