G = (<sunny, ?, ?, ?> ; <?, warm, ?, ?> ; <?, ?, high, ?>). Training data = <sunny, warm, normal, same> => Yes (positive example). How will G be represented after encountering this training data?

Initially, third hypothesis in set G states that irrespective of other attributes, if third attribute is high, the example is positive and it is negative, otherwise. But, in the given example, third attribute is normal (not high), but still the example is positive. Thus, the third hypothesis is incorrect. So, it is discarded.