datetime64[ns] is a general dtype, while <M8[ns] is a specific dtype. General dtypes map to specific dtypes, but may be different from one installation of NumPy to the next.
On a machine whose byte order is little endian, there is no difference between np.dtype('datetime64[ns]') and np.dtype('<M8[ns]'):
In [6]: np.dtype('datetime64[ns]') == np.dtype('<M8[ns]')
Out[6]: True
However, on a big endian machine, np.dtype('datetime64[ns]') would equal np.dtype('>M8[ns]').
So datetime64[ns] maps to either <M8[ns] or >M8[ns] depending on the endian-ness of the machine.
There are many other similar examples of general dtypes mapping to specific dtypes: int64 maps to <i8 or >i8, and int maps to either int32 or int64 depending on the bit architecture of the OS and how NumPy was compiled.
Apparently, the repr of the datetime64 dtype has change since the time the book was written to show the endian-ness of the dtype.