Usually, the model would take the risk of over-fitting if it is only optimized upon the target attributes due to unavoidable noises in the dataset.
the Multi-task learning implicitly increases training data of other relevant tasks having different noise patterns and can average these noise patterns to obtain a more general representation and thus improve generalization of the model.