Linear separable means that there is a hyperplane
This means that there is a hyperplane, which splits your input data into two half-spaces such that all points of the first class should be in one half-space and other points of the second class should be in the other half-space.
In two dimensional space, it means that there is a line, which separates points of one class from points of the other class.
For example: In the following image, if blue circles represent points from one class and red circles represent points from the other class, then these points are linearly separable.
In three dimensions, it means that there is a plane that separates points of one class from points of the other class.
Hope this answer helps.
Visit this Neural Network Tutorial to know more about Neural Network.