Yolo tries to find objects in the image. It outputs predictions in the form of boxes. Each box has a coordinate x,y which determines its location. It also has a width and a height which determines the predictions size. That’s the basics. If you want to understand it deeper, have a look at this blog or google around  Good luck!
Edit: I also like this guys blog posts
Edit2: Shit, I misread the question. The ... means that it slices in all the dimensions that aren’t specified. In this case it’s all the dimension but the last. It’s basically doing prediction[:,:,:,:,0]