Why does prediction by a consensus of classifier work better than prediction by a single classifiers?

Question

I have seen that consensus of classifiers (taking say 5 separate classifiers) and obtaining the final labeling of the unknown sample based on the voting method (whichever class gets the predicted the most is the class of the unknown sample) works better than taking a single classifier for predicting the class of a sample. Why so? Any articles which show why this happens?