Machine epsilon vs least positive number
Machine epsilon is the relative error (the error independent of what exponent you are currently using.)

It tells you the maximum error in the mantissa after a given operation.  For example take sqrt(2.0) and sqrt(2048.0) = sqrt(2.0)*32.0.  In IEEE 754 double precision (53-bit mantissa) the maximum error in the mantissa for this result will be $2^{-53} \approx 1.11\times10^{-16}$.

Put another way, to quote Wikipedia, the machine epsilon is


  the maximum spacing between a normalised floating point number, $x$, and an adjacent normalised number is $2 \epsilon \times |x|$.


The least positive number in a floating point system includes the exponent.  In double precision IEEE 754 the smallest normalized number is $2^{-1022} \approx 2.225 \times 10^{-308}$.  The smallest denormalized number is $2^{-52}\times 2^{-1022}=2^{-1074}\approx 4.941\times 10^{-324}$.