Machine learning is the process by which a system learns by itself without programming. The main goal of machine learning is to answer a question based on the data model that was created during the process of machine learning.
Let's say that we have a climate and weather dataset that has a correlation between temperature, humidity, and rainfall. The machine would observe this dataset using various algorithms and would generate a data model. A data model is the gist of the dataset, which can then be used to answer questions such as, "If the temperature is x and the humidity is y, will it rain?"
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I may have over-simplified ML, but this is what lies at its core.
Tom M. Mitchell (http://www.cs.cmu.edu/~tom/) defined ML as the following:
"A computer program is said to learn from experience E with respect to some class of tasks T and performance...
