Removing Bounded Noise from an Audio Signal
If you have some prior information about your noise e.g frequency band, you can simply implement an noise removing algorithm with emphasis on removing the noise on that band (I mean use a somehow weighted noise removing process).

One of nice methods is weighted multi-band spectral subtraction (this is not the only method and in fact these weighted methods have many variations).
The improvement of MBSS is due to the fact that the multi-band speech takes into account the non-linear effect of coloured noise on the spectrum of speech i.e. some frequencies are affected more adversely than others.
Multi-band spectral subtraction (MBSS) method provides a definite improvement over other methods such as the conventional power spectral subtraction method.

Speech spectrum is divided into $N$ non-overlapping bands and spectral subtraction is applied to each band independently. The estimation of the clean speech spectrum in $i$'th band can be obtained from:

$$|x(\omega)|^2=|y(\omega)|^2 – \alpha_i \delta_i |d(\omega)|^2$$

for

$c_i&lt;\omega&lt;c_{i+1}$

Where $ c_i $ and $ c_{i+1}$ are the beginning and ending frequency band (your specific band) respectively. In the $i$'th band, $\alpha_i$ is the over-subtraction factor and $\delta_i$  is factor to control noise removal properties in each band individually. So you can set coefficient to remove the bounded noise from an audio signal.

For more help, you can read this paper :


  Sunil D. Kamath, Philipos C. Loizou, “A multi-band spectral
  subtraction method for enhancing speech corrupted by colored noise,”
   Proc. IEEE Int. Conf. Acoust., Speech, Signal Process., vol. 4, July 2002.