'Machine Learning' is a field of Computer Sciences that considers Artificial Intelligence Software & it's construction.
This software has capability to learn, or in simple terms: a capability to increase quality of it's tasks performance, based on experiences from past.
Program that learns can be imagined as program that uses abstract algorithm that needs concretization to perform certain tasks. Such algorithm needs to be filled with details that are not known beforehand.
Learning is transforming these 'empty places' into algorithm that fulfills needs of a constructor by choosing proper parameters (details) to fill the 'empty places'.
These parameters, acquired during the learning process, are named 'knowledges' or 'skills'.
Algorithms for acquiring or perfecting 'knowledges' or 'skills' are named 'Learning Algorithms'.
In Literature there are very many of learning algorithms. These can be categorized according to 'knowledges' or 'skills' data representation, tasks types for which 'knowledges' or 'skills' are used, as well as by the method(s) of acquisition for 'experiences' - named 'training information'.
Main motivation to learn AI would be to handle algorithms too complex & unknown to handle precisely, including software handling unknown environment influences, as for example robot navigation on the real streets - there are too many unknown factors as holes in ground or wind or animals, weather changes etc.
Second main motivation is handling tasks with too many parameters to handle, too expensive to execute precisely.
Thrid main motivation is that is a rewarding subject, well documented in a proper literature, but challenging still. Lot of possibilities to earn praise, from scientific works to PhD subjects.
See also, if You wish: Learning Definition, Programs Learning, Neural Networks, Artificial Intelligence Learning Aspects, An Example Design of Artificial Intelligence for Martial Arts.