When $\Omega=\mathbb R^N$ and $\sigma \in(0,1)$, one has the following identity:
$$
\iint_{\mathbb R^N\times \mathbb R^N} \frac{ |u(x+y)-u(x)|^2}{|y|^{N+2\sigma}}\, dxdy = C_N \int_{\mathbb R^N} |\xi|^{2\sigma} |\hat{u}(\xi)|^2\, d\xi,$$
where $C_N> 0$ is a constant depending on the spatial dimension $N$ only. In particular, if $m\in \mathbb N$, one can write the Sobolev norm for $H^{m+\sigma}(\mathbb R^N)=W^{m+\sigma, 2}(\mathbb R^N)$ in the following form:
$$
\| u\|_{H^{k+\sigma}(\mathbb R^N)}^2 = \sum_{|\alpha|\le m} \| \partial^\alpha u \|_{L^2}^2 + \sum_{|\alpha|=m}
\iint_{\mathbb R^N\times \mathbb R^N} \frac{ |\partial^\alpha u(x+y)-\partial^\alpha u(x)|^2}{|y|^{N+2\sigma}}\, dxdy.$$
This formulation does not make use of the Fourier transform, which is only available on the free space $\mathbb R^N$, and can therefore be generalized to Sobolev spaces on domains.
Proof (Taken from Bahouri-Chemin-Danchin, proposition 1.37).
By Plancherel's identity, one has
$$\tag{1}
\int_{\mathbb R^N} \frac{|u(x+y)-u(x)|^2}{|y|^{N+2\sigma}}\, dx = C_N \int_{\mathbb R^N} \frac{ |e^{i y\cdot \xi}-1|^2}{|y|^{N+2\sigma}} |\hat{u}(\xi)|^2\, d\xi. $$
The function
$$
F(\xi)=\int_{\mathbb R^N} \frac{ |e^{i y\cdot \xi}-1|^2}{|y|^{N+2\sigma}} \, dy$$
is radially symmetric and homogeneous of degree $2\sigma$, so $F(\xi)=C|\xi|^{2\sigma}$. Integrating (1) and using Fubini's theorem one obtains the desired conclusion. $\square$.
EDIT 2025. Reading this answer again after nine years, I do not fully agree with it anymore. Sure, what I said explains the case $p=2, \Omega=\mathbb R^N.$ But in general, the real reason why people defined that norm is more likely to be related to interpolation. These spaces probably arise as interpolation spaces of the $W^{m,p}(\Omega)$ spaces when $m$ is an integer.