Answer -

In a multi-class classification problem, the classification task has more than two mutually exclusive classes whereas in a multi-label problem each label has a different classification task, however, the tasks are related somehow. For example, classifying a set of images of animals which may be cats, dogs, or bears is a multi-class classification problem that assumes that each sample has only one label meaning an image can be classified as either a cat or a dog but not both at the same time. Now imagine that you want to process the below image. The image shown below needs to be classified as both cat and dog because the image shows both the animals. In a multi-label classification problem, a set of labels are assigned to each sample and the classes are not mutually exclusive. So, a pattern can belong to one or more classes in a multi-label classification problem.