I can understand what meaningful data is like its important information that can be used to evaluate something but I don't get what non-meaningful data is? Is it less important data?
"meaningful" is a vague word anyway, but yes you got the idea: in the context of a particular task meaningful data is the information which contributes to solving the task. Non-meaningful is the opposite, so information which doesn't help for the task. Sometimes non-meaningful data makes it harder to the ML algorithm to capture the relevant information, since it has to correctly identify what is meaningful and what is not (as opposed to the case where it's provided only with relevant information).
Example: if you want to predict how fast a car can go, engine type and manufacturer are meaningful data. Colour is not.