Conv kernels operate on the whole input channels as described in your link.
The out_channels give the number of different kernels used.
So in your first conv layer you are using 6 different kernels with a size of [3, 5, 5].
In other words, each kernel has a spatial size of 5 and a depth of 3, since your input volume has 3 channels.