What are tokens and tokenizations?
Well, I think it is better to watch a course about it. 
But, for instance, when people comment on different products on Amazon, there is a way to understand are their comments positive or negative, therefore their comments are used as data, analyzed and then labeled as positive or negative. Further, using this approach, one can find whether an email is spam or not, etc.

In order to analyze a text, we need to split it into its elements, meaning, its words (usually) each of these elements is called a token. 

after splitting the text to words, useless words that do not represent anything, some signs, etc (the, ".", "my",...) are omitted, then we create bags of words, that are the most important words in the whole dataset (all comments), then each word is a column in the table and each row of the table is a comment and has 1 in a column if it contains that specific word. there is also a label column that shows if the comment is positive or not. then having this dataset, we can fit a classification model to the dataset.