The human involvement in the formulation of the problems ensures this. As a simple thought experiment in support of this proposition, consider a learning task for which the class attribute is generated by a random number generator and in no way relates to the other attributes. The majority of machine learning researchers would not be in the slightest disconcerted if their systems failed to perform well when trained on such data. As a further example, consider a learning task for which the class attribute is a simple count of the number of missing attribute values for an object. Again, the majority of machine learning researchers would be unconcerned that their systems failed to perform well in such circumstances.
Machine learning is simply unsuited to such tasks.
A knowledgeable user would not apply machine learning to such data, at least not in the expectation of obtaining a useful classifier therefrom.