Partial pooling is a statistical technique used in hierarchical modeling to balance between individual group estimates and the overall population estimate, reducing the risk of overfitting by borrowing strength from the entire dataset. It is particularly useful in situations with small sample sizes or when individual group estimates are noisy, allowing for more stable and reliable inferences.