Your initial data was roatated in the existing three dimensions such that the bulk of the variance was along the X axis, then rotated again such that the remaining variance was predominantly along the Y axis. Then the Z axis was flattened so only the new X and Y axes remained.
This article goes into a really good and accessible explanation of what is going on in PCA, I recommend you check it out: http://www.cs.otago.ac.nz/cosc453/student_tutorials/principal_components.pdf